The interval estimate of the mean value of y for a given value of x is defined as? a) Prediction interval estimate b) Confidence interval estimate c) Average regression d) X vs Y correlation interval
If the coefficient of determination is a positive value, then the coefficient of correlation a) Must also be positive b) Must be zero c) Can be either negative or positive d) Must be larger than 1
Which of the following is true about multiple regression model? a) It has only one independent variable b) It has more than one dependent variable c) It has more than one independent variable d) It has at least 2 dependent variables
In a multiple regression model, the error term ɛ is assumed to a) Have a mean of 1 b) Have a variance of 0 c) Have a standard deviation of 1 d) Be normally distributed
Regression analysis is a statistical procedure for developing a mathematical equation that describes how a) One independent and one or more dependent variables are related b) Several independent and several dependent variables are related c) One dependent and one or more independent variables are related d) None of these alternatives correct
If the R.sq value is small for a model with a large number of independent variables, the adjusted coefficient of determination _______________ a) Can be positive b) Can be negative c) Is zero d) Can’t say
Which one of the statements is true regarding residuals in regression analysis? a) Mean of residuals is always 0 b) Mean of residuals is always < 0 c) Mean of residuals is always > 0 d) There is no such rule for residuals
In a simple linear regression model (one independent variable), if we change the input variable by 1 unit, how much will the output variable change? a) By 1 b) No change c) By its slope d) None of these
If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on these data is a) 0 b) 1 c) Either 1 or -1, depending upon whether the relationship is positive d) Could be any value between -1 and 1
In a regression analysis, the regression equation is given by y = 12 – 6x. If SSE = 510 and SST = 1000, then the coefficient of correlation is a) -0.7 b) +0.7 c) 0.49 d) -0.49
